The ability to edit video is currently supported by a wide variety of video editor programs. One important aspect of video editing is the ability to identify key frames (instances) in a video and to index those key moments. This provides a convenient basis for a user or viewer to navigate quickly through a video when viewing or editing the video. However, the ability to automatically identify these key frames is difficult, and if performed manually, presents a very laborious process for the user.
Many present day editors provide classification of a video into segments (“scenes”) based upon changes in the video stream of the video being edited. For example, a transition between one scene and another may be determined based on the identification of a significant change in the video stream. However, such segmentation of a video into scenes based upon significant changes does not attempt to identify interesting or important moments in a video, which may not necessarily be correlated with the change in the video stream that triggers the delineation of a scene. Consequently, after the editor has segmented the video into multiple scenes, one or more scenes may have multiple interesting moments or none at all.
Other schemes have been proposed in which audio may be used to assist in the identification of key moments in an audio track that may be used to determine keyframes in a video. However, such methods may still be limited in their ability to determine keyframes in a video.
Accordingly, there may be a need for improved techniques and apparatus to solve these and other problems.